BN4004 Operation and Supply Chain Analytics Syllabus:
BN4004 Operation and Supply Chain Analytics Syllabus – Anna University PG Syllabus Regulation 2021
OBJECTIVE:
➢ To treat the subject in depth by emphasizing on the advanced quantitative models and methods in logistics and supply chain management and its practical aspects and the latest developments in the field.
UNIT- I INTRODUCTION
Introduction to analytics – descriptive, predictive and prescriptive analytics, Data Driven Supply Chains – Basics, transforming supply chains, Barriers to implementation, Road Map.
UNIT- II WAREHOUSING DECISIONS
Mathematical Programming Models – P-Median Methods – Guided LP Approach – Balmer – Wolfe Method, Greedy Drop Heuristics, Dynamic Location Models, Space Determination and Layout Methods
UNIT- III INVENTORY MANAGEMENT
Inventory aggregation Models, Dynamic Lot sizing Methods, Multi-Echelon Inventory models, Aggregate Inventory system and LIMIT, Risk Analysis in Supply Chain – Measuring transit risks, supply risks, delivering risks, Risk pooling strategies.
UNIT- IV TRANSPORTATION NETWORK MODELS
Notion of Graphs, Minimal Spanning Tree, Shortest Path Algorithms, Maximal Flow Problems, Multistage Transshipment and Transportation Problems, Set covering and Set Partitioning Problems, Traveling Salesman Algorithms, Advanced Vehicle Routing Problem Heuristics, Scheduling Algorithms-Deficit function Approach and Linking Algorithms.
UNIT- V MCDMMODELS
Analytic Hierarchy Process(AHP), Data Envelopment Analysis (DEA), Fuzzy Logic and Techniques, the analytical network process (ANP), TOPSIS-Application in SCM.
TOTAL: 45 PERIODS
COURSE OUTCOMES:
➢ To enable quantitative solutions in business decision making under conditions of certainty, risk and uncertainty.
REFERENCES:
1. Nada R. Sanders, Big data driven supply chain management: A framework for implementing analytics and turning information into intelligence, Pearson Education, 2014.
2. Michael Watson, Sara Lewis, Peter Cacioppi, Jay Jayaraman, Supply Chain Network Design: Applying Optimization and Analytics to the Global Supply Chain, Pearson Education, 2013.
3. Anna Nagurney, Min Yu, Amir H. Masoumi, Ladimer S. Nagurney, Networks Against Time: Supply Chain Analytics for Perishable Products, Springer, 2013.
4. Kurt Y. Liu, Supply Chain Analytics: Concepts, Techniques and Applications Springer Nature, 7 Apr 2022.
5. Muthu Mathirajan, Chandrasekharan Rajendran, Sowmya narayanan Sadagopan, Arunachalam Ravindran, Parasuram Balasubramanian, Analytics inOperations/Supply Chain Management, I.K. International Publishing House Pvt. Ltd., 2016.